Model predictive approaches for cost-efficient building climate control with seasonal energy storage

Due to the increasing share of fluctuating renewable energy, a seasonal energy storage with high capacity is needed, which stores summer surplus electricity satisfy winter heating demand. It assumed that control integration novel thermochemical concept into building system can meet this requirement and save operating costs. For purpose, model-predictive prediction horizon beyond public weather forecasts crucial. A state-based model developed consisting building, water buffer heat supply. To assess effects storage, different supply configurations are considered. On basis, two Model Predictive Control (MPC) concepts designed efficiently operate over one year. Since reliable in time range several days, test reference year data used approximate forecast period. Additionally, hierarchy comprised superordinate optimal generation scheduling (OGS) subordinate MPC. The follow scheduled long-term lime trajectory realise possible short-term yields based on current forecast. tracking formulated either objective function or constraints. module allows reduction costs 18% realistic scenario up 80% case highly prices. This potential fully exploited by approaches, but it very sensitive change controller parameters, fluctuation price data. Moreover, applying objective-based approach, higher-level could be avoided. Through results work, confirmed greatly reduce annual not crucial apply forecasts.